{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Power transformation"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import pandas as pd\n",
    "\n",
    "# for plotting\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "# for Q-Q plots\n",
    "import scipy.stats as stats\n",
    "\n",
    "# the dataset for the demo\n",
    "from sklearn.datasets import fetch_california_housing\n",
    "\n",
    "# with open-source packages\n",
    "from sklearn.preprocessing import FunctionTransformer\n",
    "from feature_engine.transformation import PowerTransformer"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>MedInc</th>\n",
       "      <th>HouseAge</th>\n",
       "      <th>AveRooms</th>\n",
       "      <th>AveBedrms</th>\n",
       "      <th>Population</th>\n",
       "      <th>AveOccup</th>\n",
       "      <th>Latitude</th>\n",
       "      <th>Longitude</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>8.3252</td>\n",
       "      <td>41.0</td>\n",
       "      <td>6.984127</td>\n",
       "      <td>1.023810</td>\n",
       "      <td>322.0</td>\n",
       "      <td>2.555556</td>\n",
       "      <td>37.88</td>\n",
       "      <td>-122.23</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>8.3014</td>\n",
       "      <td>21.0</td>\n",
       "      <td>6.238137</td>\n",
       "      <td>0.971880</td>\n",
       "      <td>2401.0</td>\n",
       "      <td>2.109842</td>\n",
       "      <td>37.86</td>\n",
       "      <td>-122.22</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>7.2574</td>\n",
       "      <td>52.0</td>\n",
       "      <td>8.288136</td>\n",
       "      <td>1.073446</td>\n",
       "      <td>496.0</td>\n",
       "      <td>2.802260</td>\n",
       "      <td>37.85</td>\n",
       "      <td>-122.24</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>5.6431</td>\n",
       "      <td>52.0</td>\n",
       "      <td>5.817352</td>\n",
       "      <td>1.073059</td>\n",
       "      <td>558.0</td>\n",
       "      <td>2.547945</td>\n",
       "      <td>37.85</td>\n",
       "      <td>-122.25</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>3.8462</td>\n",
       "      <td>52.0</td>\n",
       "      <td>6.281853</td>\n",
       "      <td>1.081081</td>\n",
       "      <td>565.0</td>\n",
       "      <td>2.181467</td>\n",
       "      <td>37.85</td>\n",
       "      <td>-122.25</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   MedInc  HouseAge  AveRooms  AveBedrms  Population  AveOccup  Latitude  \\\n",
       "0  8.3252      41.0  6.984127   1.023810       322.0  2.555556     37.88   \n",
       "1  8.3014      21.0  6.238137   0.971880      2401.0  2.109842     37.86   \n",
       "2  7.2574      52.0  8.288136   1.073446       496.0  2.802260     37.85   \n",
       "3  5.6431      52.0  5.817352   1.073059       558.0  2.547945     37.85   \n",
       "4  3.8462      52.0  6.281853   1.081081       565.0  2.181467     37.85   \n",
       "\n",
       "   Longitude  \n",
       "0    -122.23  \n",
       "1    -122.22  \n",
       "2    -122.24  \n",
       "3    -122.25  \n",
       "4    -122.25  "
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# load the California House price data from Scikit-learn\n",
    "X, y = fetch_california_housing(return_X_y=True, as_frame=True)\n",
    "\n",
    "# display top 5 rows\n",
    "X.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Plot histogram and Q-Q plots to explore the variable distribution\n",
    "\n",
    "\n",
    "def diagnostic_plots(df, variable):\n",
    "\n",
    "    # function to plot a histogram and a Q-Q plot\n",
    "    # side by side, for a certain variable\n",
    "\n",
    "    plt.figure(figsize=(15, 6))\n",
    "\n",
    "    # histogram\n",
    "    plt.subplot(1, 2, 1)\n",
    "    df[variable].hist(bins=30)\n",
    "    plt.title(f\"Histogram of {variable}\")\n",
    "\n",
    "    # q-q plot\n",
    "    plt.subplot(1, 2, 2)\n",
    "    stats.probplot(df[variable], dist=\"norm\", plot=plt)\n",
    "    plt.title(f\"Q-Q plot of {variable}\")\n",
    "\n",
    "    plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "plt.rcParams[\"figure.dpi\"] = 450"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x432 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# check original distribution (not included in this recipe of book)\n",
    "\n",
    "diagnostic_plots(X, \"MedInc\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x432 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "diagnostic_plots(X, \"Population\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Power transformation with NumPy"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "# make a copy of the dataframe where we will store the modified\n",
    "# variables\n",
    "\n",
    "X_tf = X.copy()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "# make a list with the variables to transform\n",
    "\n",
    "variables = [\"MedInc\", \"Population\"]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "# apply a 0.3 exponent power transformation to a set of variables\n",
    "\n",
    "X_tf[variables] = np.power(X[variables], 0.3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x432 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# check the distribution of the transformed variable\n",
    "\n",
    "diagnostic_plots(X_tf, \"MedInc\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x432 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "diagnostic_plots(X_tf, \"Population\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Power transformation with Scikit-learn"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "# make a copy of the dataframe where we will store the modified\n",
    "# variables\n",
    "\n",
    "X_tf = X.copy()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "# set up the transformer with a user defined function, in this\n",
    "# case the 0.3 power transformation\n",
    "\n",
    "transformer = FunctionTransformer(lambda x: np.power(x, 0.3))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [],
   "source": [
    "# transform slice of dataframe with indicated variables\n",
    "\n",
    "X_tf[variables] = transformer.transform(X[variables])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x432 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# visualize the transformation (not in book)\n",
    "\n",
    "diagnostic_plots(X_tf, \"MedInc\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x432 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "diagnostic_plots(X_tf, \"Population\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Power transformation with Feature-engine"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<style>#sk-container-id-1 {\n",
       "  /* Definition of color scheme common for light and dark mode */\n",
       "  --sklearn-color-text: black;\n",
       "  --sklearn-color-line: gray;\n",
       "  /* Definition of color scheme for unfitted estimators */\n",
       "  --sklearn-color-unfitted-level-0: #fff5e6;\n",
       "  --sklearn-color-unfitted-level-1: #f6e4d2;\n",
       "  --sklearn-color-unfitted-level-2: #ffe0b3;\n",
       "  --sklearn-color-unfitted-level-3: chocolate;\n",
       "  /* Definition of color scheme for fitted estimators */\n",
       "  --sklearn-color-fitted-level-0: #f0f8ff;\n",
       "  --sklearn-color-fitted-level-1: #d4ebff;\n",
       "  --sklearn-color-fitted-level-2: #b3dbfd;\n",
       "  --sklearn-color-fitted-level-3: cornflowerblue;\n",
       "\n",
       "  /* Specific color for light theme */\n",
       "  --sklearn-color-text-on-default-background: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, black)));\n",
       "  --sklearn-color-background: var(--sg-background-color, var(--theme-background, var(--jp-layout-color0, white)));\n",
       "  --sklearn-color-border-box: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, black)));\n",
       "  --sklearn-color-icon: #696969;\n",
       "\n",
       "  @media (prefers-color-scheme: dark) {\n",
       "    /* Redefinition of color scheme for dark theme */\n",
       "    --sklearn-color-text-on-default-background: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, white)));\n",
       "    --sklearn-color-background: var(--sg-background-color, var(--theme-background, var(--jp-layout-color0, #111)));\n",
       "    --sklearn-color-border-box: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, white)));\n",
       "    --sklearn-color-icon: #878787;\n",
       "  }\n",
       "}\n",
       "\n",
       "#sk-container-id-1 {\n",
       "  color: var(--sklearn-color-text);\n",
       "}\n",
       "\n",
       "#sk-container-id-1 pre {\n",
       "  padding: 0;\n",
       "}\n",
       "\n",
       "#sk-container-id-1 input.sk-hidden--visually {\n",
       "  border: 0;\n",
       "  clip: rect(1px 1px 1px 1px);\n",
       "  clip: rect(1px, 1px, 1px, 1px);\n",
       "  height: 1px;\n",
       "  margin: -1px;\n",
       "  overflow: hidden;\n",
       "  padding: 0;\n",
       "  position: absolute;\n",
       "  width: 1px;\n",
       "}\n",
       "\n",
       "#sk-container-id-1 div.sk-dashed-wrapped {\n",
       "  border: 1px dashed var(--sklearn-color-line);\n",
       "  margin: 0 0.4em 0.5em 0.4em;\n",
       "  box-sizing: border-box;\n",
       "  padding-bottom: 0.4em;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "}\n",
       "\n",
       "#sk-container-id-1 div.sk-container {\n",
       "  /* jupyter's `normalize.less` sets `[hidden] { display: none; }`\n",
       "     but bootstrap.min.css set `[hidden] { display: none !important; }`\n",
       "     so we also need the `!important` here to be able to override the\n",
       "     default hidden behavior on the sphinx rendered scikit-learn.org.\n",
       "     See: https://github.com/scikit-learn/scikit-learn/issues/21755 */\n",
       "  display: inline-block !important;\n",
       "  position: relative;\n",
       "}\n",
       "\n",
       "#sk-container-id-1 div.sk-text-repr-fallback {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       "div.sk-parallel-item,\n",
       "div.sk-serial,\n",
       "div.sk-item {\n",
       "  /* draw centered vertical line to link estimators */\n",
       "  background-image: linear-gradient(var(--sklearn-color-text-on-default-background), var(--sklearn-color-text-on-default-background));\n",
       "  background-size: 2px 100%;\n",
       "  background-repeat: no-repeat;\n",
       "  background-position: center center;\n",
       "}\n",
       "\n",
       "/* Parallel-specific style estimator block */\n",
       "\n",
       "#sk-container-id-1 div.sk-parallel-item::after {\n",
       "  content: \"\";\n",
       "  width: 100%;\n",
       "  border-bottom: 2px solid var(--sklearn-color-text-on-default-background);\n",
       "  flex-grow: 1;\n",
       "}\n",
       "\n",
       "#sk-container-id-1 div.sk-parallel {\n",
       "  display: flex;\n",
       "  align-items: stretch;\n",
       "  justify-content: center;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "  position: relative;\n",
       "}\n",
       "\n",
       "#sk-container-id-1 div.sk-parallel-item {\n",
       "  display: flex;\n",
       "  flex-direction: column;\n",
       "}\n",
       "\n",
       "#sk-container-id-1 div.sk-parallel-item:first-child::after {\n",
       "  align-self: flex-end;\n",
       "  width: 50%;\n",
       "}\n",
       "\n",
       "#sk-container-id-1 div.sk-parallel-item:last-child::after {\n",
       "  align-self: flex-start;\n",
       "  width: 50%;\n",
       "}\n",
       "\n",
       "#sk-container-id-1 div.sk-parallel-item:only-child::after {\n",
       "  width: 0;\n",
       "}\n",
       "\n",
       "/* Serial-specific style estimator block */\n",
       "\n",
       "#sk-container-id-1 div.sk-serial {\n",
       "  display: flex;\n",
       "  flex-direction: column;\n",
       "  align-items: center;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "  padding-right: 1em;\n",
       "  padding-left: 1em;\n",
       "}\n",
       "\n",
       "\n",
       "/* Toggleable style: style used for estimator/Pipeline/ColumnTransformer box that is\n",
       "clickable and can be expanded/collapsed.\n",
       "- Pipeline and ColumnTransformer use this feature and define the default style\n",
       "- Estimators will overwrite some part of the style using the `sk-estimator` class\n",
       "*/\n",
       "\n",
       "/* Pipeline and ColumnTransformer style (default) */\n",
       "\n",
       "#sk-container-id-1 div.sk-toggleable {\n",
       "  /* Default theme specific background. It is overwritten whether we have a\n",
       "  specific estimator or a Pipeline/ColumnTransformer */\n",
       "  background-color: var(--sklearn-color-background);\n",
       "}\n",
       "\n",
       "/* Toggleable label */\n",
       "#sk-container-id-1 label.sk-toggleable__label {\n",
       "  cursor: pointer;\n",
       "  display: block;\n",
       "  width: 100%;\n",
       "  margin-bottom: 0;\n",
       "  padding: 0.5em;\n",
       "  box-sizing: border-box;\n",
       "  text-align: center;\n",
       "}\n",
       "\n",
       "#sk-container-id-1 label.sk-toggleable__label-arrow:before {\n",
       "  /* Arrow on the left of the label */\n",
       "  content: \"▸\";\n",
       "  float: left;\n",
       "  margin-right: 0.25em;\n",
       "  color: var(--sklearn-color-icon);\n",
       "}\n",
       "\n",
       "#sk-container-id-1 label.sk-toggleable__label-arrow:hover:before {\n",
       "  color: var(--sklearn-color-text);\n",
       "}\n",
       "\n",
       "/* Toggleable content - dropdown */\n",
       "\n",
       "#sk-container-id-1 div.sk-toggleable__content {\n",
       "  max-height: 0;\n",
       "  max-width: 0;\n",
       "  overflow: hidden;\n",
       "  text-align: left;\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-1 div.sk-toggleable__content.fitted {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-1 div.sk-toggleable__content pre {\n",
       "  margin: 0.2em;\n",
       "  border-radius: 0.25em;\n",
       "  color: var(--sklearn-color-text);\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-1 div.sk-toggleable__content.fitted pre {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-1 input.sk-toggleable__control:checked~div.sk-toggleable__content {\n",
       "  /* Expand drop-down */\n",
       "  max-height: 200px;\n",
       "  max-width: 100%;\n",
       "  overflow: auto;\n",
       "}\n",
       "\n",
       "#sk-container-id-1 input.sk-toggleable__control:checked~label.sk-toggleable__label-arrow:before {\n",
       "  content: \"▾\";\n",
       "}\n",
       "\n",
       "/* Pipeline/ColumnTransformer-specific style */\n",
       "\n",
       "#sk-container-id-1 div.sk-label input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
       "  color: var(--sklearn-color-text);\n",
       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
       "}\n",
       "\n",
       "#sk-container-id-1 div.sk-label.fitted input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
       "  background-color: var(--sklearn-color-fitted-level-2);\n",
       "}\n",
       "\n",
       "/* Estimator-specific style */\n",
       "\n",
       "/* Colorize estimator box */\n",
       "#sk-container-id-1 div.sk-estimator input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
       "}\n",
       "\n",
       "#sk-container-id-1 div.sk-estimator.fitted input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-2);\n",
       "}\n",
       "\n",
       "#sk-container-id-1 div.sk-label label.sk-toggleable__label,\n",
       "#sk-container-id-1 div.sk-label label {\n",
       "  /* The background is the default theme color */\n",
       "  color: var(--sklearn-color-text-on-default-background);\n",
       "}\n",
       "\n",
       "/* On hover, darken the color of the background */\n",
       "#sk-container-id-1 div.sk-label:hover label.sk-toggleable__label {\n",
       "  color: var(--sklearn-color-text);\n",
       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
       "}\n",
       "\n",
       "/* Label box, darken color on hover, fitted */\n",
       "#sk-container-id-1 div.sk-label.fitted:hover label.sk-toggleable__label.fitted {\n",
       "  color: var(--sklearn-color-text);\n",
       "  background-color: var(--sklearn-color-fitted-level-2);\n",
       "}\n",
       "\n",
       "/* Estimator label */\n",
       "\n",
       "#sk-container-id-1 div.sk-label label {\n",
       "  font-family: monospace;\n",
       "  font-weight: bold;\n",
       "  display: inline-block;\n",
       "  line-height: 1.2em;\n",
       "}\n",
       "\n",
       "#sk-container-id-1 div.sk-label-container {\n",
       "  text-align: center;\n",
       "}\n",
       "\n",
       "/* Estimator-specific */\n",
       "#sk-container-id-1 div.sk-estimator {\n",
       "  font-family: monospace;\n",
       "  border: 1px dotted var(--sklearn-color-border-box);\n",
       "  border-radius: 0.25em;\n",
       "  box-sizing: border-box;\n",
       "  margin-bottom: 0.5em;\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-1 div.sk-estimator.fitted {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-0);\n",
       "}\n",
       "\n",
       "/* on hover */\n",
       "#sk-container-id-1 div.sk-estimator:hover {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
       "}\n",
       "\n",
       "#sk-container-id-1 div.sk-estimator.fitted:hover {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-2);\n",
       "}\n",
       "\n",
       "/* Specification for estimator info (e.g. \"i\" and \"?\") */\n",
       "\n",
       "/* Common style for \"i\" and \"?\" */\n",
       "\n",
       ".sk-estimator-doc-link,\n",
       "a:link.sk-estimator-doc-link,\n",
       "a:visited.sk-estimator-doc-link {\n",
       "  float: right;\n",
       "  font-size: smaller;\n",
       "  line-height: 1em;\n",
       "  font-family: monospace;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "  border-radius: 1em;\n",
       "  height: 1em;\n",
       "  width: 1em;\n",
       "  text-decoration: none !important;\n",
       "  margin-left: 1ex;\n",
       "  /* unfitted */\n",
       "  border: var(--sklearn-color-unfitted-level-1) 1pt solid;\n",
       "  color: var(--sklearn-color-unfitted-level-1);\n",
       "}\n",
       "\n",
       ".sk-estimator-doc-link.fitted,\n",
       "a:link.sk-estimator-doc-link.fitted,\n",
       "a:visited.sk-estimator-doc-link.fitted {\n",
       "  /* fitted */\n",
       "  border: var(--sklearn-color-fitted-level-1) 1pt solid;\n",
       "  color: var(--sklearn-color-fitted-level-1);\n",
       "}\n",
       "\n",
       "/* On hover */\n",
       "div.sk-estimator:hover .sk-estimator-doc-link:hover,\n",
       ".sk-estimator-doc-link:hover,\n",
       "div.sk-label-container:hover .sk-estimator-doc-link:hover,\n",
       ".sk-estimator-doc-link:hover {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-3);\n",
       "  color: var(--sklearn-color-background);\n",
       "  text-decoration: none;\n",
       "}\n",
       "\n",
       "div.sk-estimator.fitted:hover .sk-estimator-doc-link.fitted:hover,\n",
       ".sk-estimator-doc-link.fitted:hover,\n",
       "div.sk-label-container:hover .sk-estimator-doc-link.fitted:hover,\n",
       ".sk-estimator-doc-link.fitted:hover {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-3);\n",
       "  color: var(--sklearn-color-background);\n",
       "  text-decoration: none;\n",
       "}\n",
       "\n",
       "/* Span, style for the box shown on hovering the info icon */\n",
       ".sk-estimator-doc-link span {\n",
       "  display: none;\n",
       "  z-index: 9999;\n",
       "  position: relative;\n",
       "  font-weight: normal;\n",
       "  right: .2ex;\n",
       "  padding: .5ex;\n",
       "  margin: .5ex;\n",
       "  width: min-content;\n",
       "  min-width: 20ex;\n",
       "  max-width: 50ex;\n",
       "  color: var(--sklearn-color-text);\n",
       "  box-shadow: 2pt 2pt 4pt #999;\n",
       "  /* unfitted */\n",
       "  background: var(--sklearn-color-unfitted-level-0);\n",
       "  border: .5pt solid var(--sklearn-color-unfitted-level-3);\n",
       "}\n",
       "\n",
       ".sk-estimator-doc-link.fitted span {\n",
       "  /* fitted */\n",
       "  background: var(--sklearn-color-fitted-level-0);\n",
       "  border: var(--sklearn-color-fitted-level-3);\n",
       "}\n",
       "\n",
       ".sk-estimator-doc-link:hover span {\n",
       "  display: block;\n",
       "}\n",
       "\n",
       "/* \"?\"-specific style due to the `<a>` HTML tag */\n",
       "\n",
       "#sk-container-id-1 a.estimator_doc_link {\n",
       "  float: right;\n",
       "  font-size: 1rem;\n",
       "  line-height: 1em;\n",
       "  font-family: monospace;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "  border-radius: 1rem;\n",
       "  height: 1rem;\n",
       "  width: 1rem;\n",
       "  text-decoration: none;\n",
       "  /* unfitted */\n",
       "  color: var(--sklearn-color-unfitted-level-1);\n",
       "  border: var(--sklearn-color-unfitted-level-1) 1pt solid;\n",
       "}\n",
       "\n",
       "#sk-container-id-1 a.estimator_doc_link.fitted {\n",
       "  /* fitted */\n",
       "  border: var(--sklearn-color-fitted-level-1) 1pt solid;\n",
       "  color: var(--sklearn-color-fitted-level-1);\n",
       "}\n",
       "\n",
       "/* On hover */\n",
       "#sk-container-id-1 a.estimator_doc_link:hover {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-3);\n",
       "  color: var(--sklearn-color-background);\n",
       "  text-decoration: none;\n",
       "}\n",
       "\n",
       "#sk-container-id-1 a.estimator_doc_link.fitted:hover {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-3);\n",
       "}\n",
       "</style><div id=\"sk-container-id-1\" class=\"sk-top-container\"><div class=\"sk-text-repr-fallback\"><pre>PowerTransformer(exp=0.3, variables=[&#x27;MedInc&#x27;, &#x27;Population&#x27;])</pre><b>In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook. <br />On GitHub, the HTML representation is unable to render, please try loading this page with nbviewer.org.</b></div><div class=\"sk-container\" hidden><div class=\"sk-item\"><div class=\"sk-estimator fitted sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-1\" type=\"checkbox\" checked><label for=\"sk-estimator-id-1\" class=\"sk-toggleable__label fitted sk-toggleable__label-arrow fitted\">&nbsp;PowerTransformer<span class=\"sk-estimator-doc-link fitted\">i<span>Fitted</span></span></label><div class=\"sk-toggleable__content fitted\"><pre>PowerTransformer(exp=0.3, variables=[&#x27;MedInc&#x27;, &#x27;Population&#x27;])</pre></div> </div></div></div></div>"
      ],
      "text/plain": [
       "PowerTransformer(exp=0.3, variables=['MedInc', 'Population'])"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# initialize the transformer with the variables to transform and\n",
    "# the desired exponent\n",
    "\n",
    "power_t = PowerTransformer(variables=variables, exp=0.3)\n",
    "\n",
    "# fit transformer to data\n",
    "power_t.fit(X)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [],
   "source": [
    "# transform selected variables\n",
    "\n",
    "X_tf = power_t.transform(X)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x432 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# check the distribution of the transformed variable\n",
    "\n",
    "diagnostic_plots(X_tf, \"MedInc\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x432 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "diagnostic_plots(X_tf, \"Population\")"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "fsml",
   "language": "python",
   "name": "fsml"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.10.5"
  },
  "toc": {
   "base_numbering": 1,
   "nav_menu": {},
   "number_sections": true,
   "sideBar": true,
   "skip_h1_title": false,
   "title_cell": "Table of Contents",
   "title_sidebar": "Contents",
   "toc_cell": false,
   "toc_position": {},
   "toc_section_display": "block",
   "toc_window_display": true
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}
